Details

Title Genetic Algorithms and Engineering Design (Engineering Design and Automation)
Author Gen, Mitsuo; Cheng, Runwei
Binding Hardback
Edition number 1st
Edition 1st Edition
Condition Used - Very good
Pages 432
Volumes 1
Language ENG
Publisher Wiley-Interscience
Publication date 1997
Illustrated Yes
Features Bibliography, Illustrated, Index
Bookseller's Inventory # L08671
ISBN 9780471127413 / 0471127418
Weight 1.51 lbs (0.68 kg)
Dimensions 9.04 x 6.64 x 1 in (22.96 x 16.87 x 2.54 cm)
Category Technology & Industrial Arts
Library of Congress subjects Mathematical optimization, Genetic algorithms
Library of Congress Catalogue Number 96008437
Dewey Decimal Code 670.285

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From the publisher

The last few years have seen important advances in the use ofgenetic algorithms to address challenging optimization problems inindustrial engineering. Genetic Algorithms and Engineering Designis the only book to cover the most recent technologies and theirapplication to manufacturing, presenting a comprehensive and fullyup-to-date treatment of genetic algorithms in industrialengineering and operations research.

Beginning with a tutorial on genetic algorithm fundamentals andtheir use in solving constrained and combinatorial optimizationproblems, the book applies these techniques to problems in specificareas--sequencing, scheduling and production plans, transportationand vehicle routing, facility layout, location-allocation, andmore. Each topic features a clearly written problem description, mathematical model, and summary of conventional heuristicalgorithms. All algorithms are explained in intuitive, rather thanhighly-technical, language and are reinforced with illustrativefigures and numerical examples.

Written by two internationally acknowledged experts in the field, Genetic Algorithms and Engineering Design features originalmaterial on the foundation and application of genetic algorithms, and also standardizes the terms and symbols used in othersources--making this complex subject truly accessible to thebeginner as well as to the more advanced reader.

Ideal for both self-study and classroom use, this self-containedreference provides indispensable state-of-the-art guidance toprofessionals and students working in industrial engineering, management science, operations research, computer science, andartificial intelligence. The only comprehensive, state-of-the-arttreatment available on the use of genetic algorithms in industrialengineering and operations research . . .

Written by internationally recognized experts in the field ofgenetic algorithms and artificial intelligence, Genetic Algorithmsand Engineering Design provides total coverage of currenttechnologies and their application to manufacturing systems.Incorporating original material on the foundation and applicationof genetic algorithms, this unique resource also standardizes theterms and symbols used in other sources--making this complexsubject truly accessible to students as well as experiencedprofessionals. Designed for clarity and ease of use, thisself-contained reference:
* Provides a comprehensive survey of selection strategies, penaltytechniques, and genetic operators used for constrained andcombinatorial optimization problems
* Shows how to use genetic algorithms to make production schedules, solve facility/location problems, make transportation/vehiclerouting plans, enhance system reliability, and much more
* Contains detailed numerical examples, plus more than 160auxiliary figures to make solution procedures transparent andunderstandable

From the rear cover

The last few years have seen important advances in the use of genetic algorithms to address challenging optimization problems in industrial engineering. Genetic Algorithms and Engineering Design is the only book to cover the most recent technologies and their application to manufacturing, presenting a comprehensive and fully up-to-date treatment of genetic algorithms in industrial engineering and operations research.

Beginning with a tutorial on genetic algorithm fundamentals and their use in solving constrained and combinatorial optimization problems, the book applies these techniques to problems in specific areas--sequencing, scheduling and production plans, transportation and vehicle routing, facility layout, location-allocation, and more. Each topic features a clearly written problem description, mathematical model, and summary of conventional heuristic algorithms. All algorithms are explained in intuitive, rather than highly-technical, language and are reinforced with illustrative figures and numerical examples.

Written by two internationally acknowledged experts in the field, Genetic Algorithms and Engineering Design features original material on the foundation and application of genetic algorithms, and also standardizes the terms and symbols used in other sources--making this complex subject truly accessible to the beginner as well as to the more advanced reader.

Ideal for both self-study and classroom use, this self-contained reference provides indispensable state-of-the-art guidance to professionals and students working in industrial engineering, management science, operations research, computer science, and artificial intelligence. The only comprehensive, state-of-the-art treatment available on the use of genetic algorithms in industrial engineering and operations research . . .

Written by internationally recognized experts in the field of genetic algorithms and artificial intelligence, Genetic Algorithms and Engineering Design provides total coverage of current technologies and their application to manufacturing systems. Incorporating original material on the foundation and application of genetic algorithms, this unique resource also standardizes the terms and symbols used in other sources--making this complex subject truly accessible to students as well as experienced professionals. Designed for clarity and ease of use, this self-contained reference:

Provides a comprehensive survey of selection strategies, penalty techniques, and genetic operators used for constrained and combinatorial optimization problems
Shows how to use genetic algorithms to make production schedules, solve facility/location problems, make transportation/vehicle routing plans, enhance system reliability, and much more
Contains detailed numerical examples, plus more than 160 auxiliary figures to make solution procedures transparent and understandable

About the author

MITSUO GEN, PhD, is a professor in the Department of Industrial andSystems Engineering at the Ashikaga Institute of Technology inJapan. An associate editor of the Engineering Design and AutomationJournal and Journal of Engineering Valuation & Cost Analysis, he is also a member of the international editorial advisory boardof Computers & Industrial Engineering. He is the author of twoother books, Linear Programming Using Turbo C and Goal ProgrammingUsing Turbo C.

RUNWEI CHENG, PhD, is a visiting associate professor at theAshikaga Institute of Technology in Japan and also an associateprofessor at the Institute of Systems Engineering at NortheastUniversity in China. Both authors are internationally known expertsin the application of genetic algorithms and artificialintelligence to the field of manufacturing systems.

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